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Identification of a Markovian system with observations corrupted by a fractional Brownian motion

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  • Mandrekar, V.
  • Naik-Nimbalkar, U.V.

Abstract

We examine the continuous time analogue of the work of [Shumway, R.H., Stoffer, D.S., 1982. An approach to time series smoothing and forecasting using EM algorithm. J. Time Ser. 3, 253-264] for state space models when the noise in the observation process is a fractional Brownian motion. We study the estimation problem for the parameter of the system process.

Suggested Citation

  • Mandrekar, V. & Naik-Nimbalkar, U.V., 2009. "Identification of a Markovian system with observations corrupted by a fractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 965-968, April.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:7:p:965-968
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    References listed on IDEAS

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    1. Kallianpur, G. & Selukar, R. S., 1991. "Parameter estimation in linear filtering," Journal of Multivariate Analysis, Elsevier, vol. 39(2), pages 284-304, November.
    2. M.L. Kleptsyna & A. Le Breton & M.-C. Roubaud, 2000. "Parameter Estimation and Optimal Filtering for Fractional Type Stochastic Systems," Statistical Inference for Stochastic Processes, Springer, vol. 3(1), pages 173-182, January.
    3. Le Breton, Alain, 1998. "Filtering and parameter estimation in a simple linear system driven by a fractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 38(3), pages 263-274, June.
    4. R. H. Shumway & D. S. Stoffer, 1982. "An Approach To Time Series Smoothing And Forecasting Using The Em Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(4), pages 253-264, July.
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